Related Experiment Video
Updated: May 4, 2026
10:00
Measurement of Lifespan in Drosophila melanogaster
Published on: January 7, 2013
34.2K
Analyzing whether countries are equally efficient at improving longevity for men and women
Douglas Barthold1, Arijit Nandi, José M Mendoza Rodríguez
1Douglas Barthold, Arijit Nandi, and José M. Mendoza Rodríguez are with the Institute for Health and Social Policy, McGill University, Montreal, Quebec. Douglas Barthold is also with the Department of Economics, McGill University. Arijit Nandi is also with the Department of Epidemiology, Biostatistics, and Occupational Health, McGill University. Jody Heymann is with the Fielding School of Public Health, University of California, Los Angeles.
American Journal of Public Health
|December 17, 2013
Summary
Healthcare spending efficiency varies significantly across countries in improving life expectancy. Increases in health expenditures were linked to greater life expectancy gains for men than for women in most Organisation for Economic Co-operation and Development countries.
Area of Science:
- Health Economics
- Public Health Policy
- Comparative Health Systems Research
Background:
- National healthcare spending is a key determinant of population health outcomes, including life expectancy.
- Understanding the efficiency of healthcare expenditure is crucial for optimizing resource allocation and improving public health.
- Previous research has not comprehensively analyzed country-specific efficiencies in healthcare spending on life expectancy for both genders.
Purpose of the Study:
- To evaluate the efficiency of country-specific healthcare spending in enhancing life expectancies for men and women.
- To identify variations in healthcare spending efficiency across developed nations.
- To determine if healthcare spending impacts male and female life expectancy differently.
Main Methods:
- Utilized multivariable regression models with country fixed-effects for 27 Organisation for Economic Co-operation and Development (OECD) countries (1991-2007).
- Controlled for time-varying national social expenditures, economic development, and health behaviors.
- Estimated the percentage change in life expectancy associated with a 1% annual increase in health expenditures.
Main Results:
- Demonstrated substantial differences in healthcare spending efficiency among OECD countries.
- A 1% annual rise in health expenditures correlated with life expectancy changes from 0.020% (USA) to 0.121% (Germany).
- Healthcare spending increases were associated with more significant life expectancy improvements for men compared to women across most OECD nations.
Conclusions:
- This study is the first to quantify the impact of country-specific health expenditures on male and female life expectancies.
- Significant variations in efficiency highlight potential for optimizing national health systems.
- Further research into the determinants of these efficiency differences can enhance equity and effectiveness in healthcare.
Related Concept Videos
01:22Applications of Life Tables
429
Life tables are versatile across various fields, providing a quantitative basis for analyzing mortality and survival rates. Whether used by demographers, actuaries, epidemiologists, or sociologists, life tables offer valuable insights into the dynamics of life and death, facilitating informed decisions in public health, insurance, conservation, and beyond. Their broad applicability highlights the interconnectedness of demographic data with practical outcomes in everyday life and strategic...
429
01:20Comparing the Survival Analysis of Two or More Groups
712
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
712
01:21Cancer Survival Analysis
863
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
863
01:22Life Tables
674
A life table is a statistical tool that summarizes the mortality and survival patterns of a population, providing detailed insights into the likelihood of survival or death across different age intervals within a cohort. By organizing data on survival probabilities and mortality rates, life tables offer a clear snapshot of population dynamics over time. They are extensively used in demography, public health, actuarial science, and ecology to analyze life expectancy, design health interventions,...
674
01:17Two-Way ANOVA
2.5K
The two-way ANOVA is an extension of the one-way ANOVA. It is a statistical test performed on three or more samples categorized by two factors - a row factor and a column factor. Ronald Fischer mentioned it in 1925 in his book 'Statistical Methods for Researchers.'
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...
2.5K
02:20Longitudinal Research
11.7K
Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
11.7K